opencompletion.com/research/activity41-game-theory-101.yaml

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31 KiB
YAML

default_max_attempts_per_step: 3
classifier_model: "MODEL_1"
feedback_model: "MODEL_1"
tokens_for_ai_rubric: |
Evaluate understanding of basic game theory concepts.
Consider:
- Grasp of strategic interaction
- Understanding of Nash equilibrium
- Recognition of dominant strategies
- Ability to analyze simple games
- Application to real-world scenarios
Provide clear explanations with examples.
sections:
- section_id: introduction
title: Welcome to Game Theory
steps:
- step_id: welcome
title: Strategic Thinking
content_blocks:
- "# Game Theory 101: The Science of Strategy 🎮🧠"
- ""
- "**Welcome to game theory!**"
- ""
- "Game theory is the study of strategic interaction - how people make decisions when their outcomes depend on others' choices."
- ""
- "**Not just for games:**"
- "- Business competition (pricing, market entry)"
- "- International relations (nuclear deterrence, trade)"
- "- Biology (evolution, animal behavior)"
- "- Economics (auctions, bargaining)"
- "- Everyday life (traffic, cooperation)"
- ""
- "**You'll learn:**"
- "✓ The Prisoner's Dilemma (cooperation vs self-interest)"
- "✓ Nash Equilibrium (stable strategies)"
- "✓ Dominant strategies (always-best moves)"
- "✓ Zero-sum vs positive-sum games"
- "✓ How to analyze strategic situations"
- ""
- "**Real applications:**"
- "- Why cartels are unstable"
- "- Why arms races happen"
- "- When cooperation emerges"
- "- How auctions should be designed"
question: Ready to learn how to think strategically about interactive decisions?
tokens_for_ai: |
Accept positive responses as 'ready'.
Language preference as 'set_language'.
Otherwise 'off_topic'.
buckets:
- ready
- set_language
- off_topic
transitions:
ready:
content_blocks:
- "Excellent! Let's start with the most famous game in game theory! 🎯"
next_section_and_step: prisoners_dilemma:step_1
set_language:
content_blocks:
- "Language preference updated!"
metadata_add:
language: "the-users-response"
counts_as_attempt: false
next_section_and_step: introduction:welcome
off_topic:
content_blocks:
- "Let's learn strategic thinking together! Ready to begin?"
counts_as_attempt: false
next_section_and_step: introduction:welcome
- section_id: prisoners_dilemma
title: The Prisoner's Dilemma
steps:
- step_id: step_1
title: The Classic Dilemma
content_blocks:
- "## The Prisoner's Dilemma: Cooperation vs Self-Interest 🚔"
- ""
- "**The Scenario:**"
- ""
- "Two criminals are arrested and interrogated separately. The prosecutor offers each the same deal:"
- ""
- "**If you both stay silent:**"
- "- Each gets 1 year in prison (light sentence, lack of evidence)"
- ""
- "**If you betray your partner but they stay silent:**"
- "- You go free (0 years)"
- "- Your partner gets 3 years"
- ""
- "**If you both betray each other:**"
- "- Each gets 2 years"
- ""
- "**Payoff matrix (years in prison - lower is better):**"
- ""
- "```"
- " Player B"
- " Silent Betray"
- "Player A Silent (-1,-1) (-3,0)"
- " Betray (0,-3) (-2,-2)"
- "```"
- ""
- "**The dilemma:**"
- "- **Collectively best:** Both stay silent (-1 each)"
- "- **Individually rational:** Both betray (-2 each)"
- ""
- "**Why betray dominates:**"
- "- If partner stays silent: Betray gets you 0 vs 1 year (betray better!)"
- "- If partner betrays: Betray gets you 2 vs 3 years (betray better!)"
- "- No matter what partner does, betraying is better for YOU"
- ""
- "**The tragedy:** Both act rationally, both end up worse off (-2 each) than if they'd cooperated (-1 each)!"
question: "You're playing prisoner's dilemma once with a stranger you'll never meet again. What should you do from a purely self-interested perspective, and why?"
tokens_for_ai: |
Correct answer: Betray (or defect/confess)
Reasoning: Betraying is a DOMINANT STRATEGY
- Dominates silence regardless of what partner does
- If partner silent: 0 years better than 1 year
- If partner betrays: 2 years better than 3 years
Look for understanding of dominant strategy.
Categorize as:
- correct_with_reasoning: Says betray AND explains dominant strategy
- correct_answer: Says betray without full explanation
- says_cooperate: Says stay silent (cooperative but not rational in one-shot)
- game_theory_aware: Mentions dilemma nature even if wrong choice
- set_language: Language preference
- off_topic: Unrelated
feedback_tokens_for_ai: |
If correct:
- Excellent! Betraying is the DOMINANT STRATEGY.
- No matter what the other player does, betraying is better for YOU.
- This is rational but leads to both getting -2 instead of -1.
- That's the tragedy of the Prisoner's Dilemma!
If says cooperate:
- Noble but not strategically optimal in a one-shot game!
- Betraying DOMINATES: better outcome regardless of partner's choice.
- In one-shot games with strangers, defection is predicted.
- (Later we'll see when cooperation can emerge in repeated games!)
Explain dominant strategy concept clearly.
buckets:
- correct_with_reasoning
- correct_answer
- says_cooperate
- game_theory_aware
- set_language
- off_topic
transitions:
correct_with_reasoning:
ai_feedback:
tokens_for_ai: |
Perfect strategic analysis!
Betraying is the DOMINANT STRATEGY - always better for you.
Even though both cooperating would be better collectively (-1 each),
individual rationality leads to mutual defection (-2 each).
This is the fundamental insight of game theory!
metadata_add:
score: "n+2"
concepts_mastered: "n+1"
next_section_and_step: prisoners_dilemma:step_2
correct_answer:
ai_feedback:
tokens_for_ai: |
Correct! Betraying is the rational choice.
Why? It's a DOMINANT STRATEGY.
No matter what your partner does, betraying gives YOU a better outcome.
If they stay silent: 0 < 1. If they betray: 2 < 3.
This individual rationality creates the dilemma!
metadata_add:
score: "n+1"
next_section_and_step: prisoners_dilemma:step_2
says_cooperate:
ai_feedback:
tokens_for_ai: |
Cooperation would be great if you could trust them!
But from pure self-interest in a ONE-SHOT game:
Betraying DOMINATES staying silent.
If they're silent: 0 years (betray) beats 1 year (silent).
If they betray: 2 years (betray) beats 3 years (silent).
Betraying is always better for YOU - that's the dilemma!
next_section_and_step: prisoners_dilemma:step_2
game_theory_aware:
ai_feedback:
tokens_for_ai: |
You sense the dilemma!
From pure self-interest: betraying DOMINATES.
It's better for you no matter what they do.
Both thinking this way → both defect → both get -2.
Could've gotten -1 each if they cooperated. That's the tragedy!
next_section_and_step: prisoners_dilemma:step_2
set_language:
content_blocks:
- "Language updated!"
metadata_add:
language: "the-users-response"
counts_as_attempt: false
next_section_and_step: prisoners_dilemma:step_1
off_topic:
content_blocks:
- "Think strategically: What gives YOU the best outcome regardless of what your partner does?"
next_section_and_step: prisoners_dilemma:step_1
- step_id: step_2
title: Real-World Dilemmas
content_blocks:
- "## Prisoner's Dilemma Everywhere! 🌍"
- ""
- "The Prisoner's Dilemma structure appears constantly:"
- ""
- "**Business cartels:**"
- "- Cooperate: Keep prices high (both profit)"
- "- Defect: Undercut price (steal market share)"
- "- Problem: Undercutting is always tempting!"
- "- Result: Cartels are unstable"
- ""
- "**Arms races:**"
- "- Cooperate: Don't build weapons (both save money)"
- "- Defect: Build weapons (get advantage if opponent doesn't)"
- "- Problem: Building weapons dominates"
- "- Result: Costly arms races"
- ""
- "**Environmental pollution:**"
- "- Cooperate: Reduce emissions (collective good)"
- "- Defect: Pollute freely (save costs)"
- "- Problem: Individual incentive to pollute"
- "- Result: Tragedy of the commons"
- ""
- "**Doping in sports:**"
- "- Cooperate: Stay clean (fair competition)"
- "- Defect: Dope (gain advantage)"
- "- Problem: If others dope, you must too to compete"
- "- Result: Widespread doping"
- ""
- "**The pattern:**"
- "Individual rationality → collectively bad outcome"
question: "Can you think of another real-world situation that has Prisoner's Dilemma structure? Describe what cooperation and defection look like."
tokens_for_ai: |
Look for recognition of the PD structure:
- Two or more parties
- Temptation to defect while others cooperate
- Mutual defection worse than mutual cooperation
- Defection is individually rational
Examples: cheating in class, tax evasion, littering, free-riding,
overfishing, etc.
Categorize as:
- excellent_example: Clear PD structure with cooperation/defection explained
- good_example: Recognizes PD structure
- vague_example: Right idea but unclear
- not_quite_pd: Example doesn't fit structure
- set_language: Language preference
- off_topic: Unrelated
feedback_tokens_for_ai: |
If they identify a good example:
- Validate it! Explain how it fits PD structure.
- Point out: cooperation better collectively, defection individually rational.
- This recognition helps understand so many social problems!
If example doesn't quite fit:
- Acknowledge the thinking.
- Explain what makes something a PD: mutual defection < mutual cooperation < defection while others cooperate.
- Offer a clearer example.
Celebrate their application of game theory!
buckets:
- excellent_example
- good_example
- vague_example
- not_quite_pd
- set_language
- off_topic
transitions:
excellent_example:
ai_feedback:
tokens_for_ai: |
Brilliant example!
Reference their specific example and confirm the PD structure.
Point out: cooperation collectively better, but defection individually tempting.
This is why so many social problems are hard to solve!
Game theory helps us recognize these structures!
metadata_add:
score: "n+2"
concepts_mastered: "n+1"
next_section_and_step: nash_equilibrium:step_1
good_example:
ai_feedback:
tokens_for_ai: |
Great example!
Confirm it has PD structure: defection tempting, but mutual defection worse.
This pattern is everywhere once you see it!
Understanding the structure helps design solutions (regulations, incentives, reputation).
metadata_add:
score: "n+1"
next_section_and_step: nash_equilibrium:step_1
vague_example:
ai_feedback:
tokens_for_ai: |
Good thinking! Clarify how their example fits:
Cooperation = ? (collectively better)
Defection = ? (individually tempting)
Help them sharpen the structure identification.
next_section_and_step: nash_equilibrium:step_1
not_quite_pd:
ai_feedback:
tokens_for_ai: |
Interesting example but not quite Prisoner's Dilemma structure.
PD needs: mutual cooperation > mutual defection, but defection dominates.
Their example might be a different game structure.
Acknowledge their thinking, explain the distinction.
next_section_and_step: nash_equilibrium:step_1
set_language:
content_blocks:
- "Language updated!"
metadata_add:
language: "the-users-response"
counts_as_attempt: false
next_section_and_step: prisoners_dilemma:step_2
off_topic:
content_blocks:
- "Think of situations where everyone would be better off cooperating, but individuals are tempted to cheat."
next_section_and_step: prisoners_dilemma:step_2
- section_id: nash_equilibrium
title: Nash Equilibrium
steps:
- step_id: step_1
title: Stable Strategies
content_blocks:
- "## Nash Equilibrium: The Stability Concept 🎯"
- ""
- "**Named after John Nash (Nobel Prize, 1994)**"
- ""
- "**Definition:**"
- "A Nash Equilibrium is a set of strategies where no player can improve their outcome by unilaterally changing their strategy."
- ""
- "**In simpler terms:**"
- "Everyone is playing their best response to what others are doing. No one wants to deviate."
- ""
- "**In Prisoner's Dilemma:**"
- "Both betraying is a Nash Equilibrium!"
- "- If A betrays, B's best response is betray (2 < 3 years)"
- "- If B betrays, A's best response is betray (2 < 3 years)"
- "- Neither wants to switch to silence unilaterally"
- ""
- "**Key insight:**"
- "Nash Equilibrium ≠ Best outcome for everyone"
- "It's just stable (self-enforcing)"
- ""
- "**Example: Coordination Game**"
- ""
- "Two friends picking where to meet:"
- "```"
- " Friend B"
- " Coffee Bar"
- "Friend A Coffee (2,2) (0,0)"
- " Bar (0,0) (1,1)"
- "```"
- ""
- "**Two Nash Equilibria:**"
- "1. Both go to Coffee (2,2)"
- "2. Both go to Bar (1,1)"
- ""
- "Meeting anywhere > missing each other!"
- "Coordination problems have multiple equilibria."
question: "In a game where two drivers approach an intersection, each can either Stop or Go. If both Go, they crash (payoff -10 each). If one Stops and one Goes, the goer gets +1 and the stopper gets 0. If both Stop, they're delayed (payoff -1 each). What are the Nash Equilibrium outcomes?"
tokens_for_ai: |
Payoff matrix:
Driver B
Stop Go
Driver A Stop (-1,-1) (0,+1)
Go (+1,0) (-10,-10)
Nash Equilibria: (Stop, Go) and (Go, Stop)
- If A stops, B's best response is Go
- If B goes, A's best response is Stop
- And vice versa for (Go, Stop)
NOT Nash Equilibrium:
- (Stop, Stop): Either could improve by switching to Go
- (Go, Go): Both would improve by switching to Stop
Look for identification of the two equilibria.
Categorize as:
- correct_both: Identifies both (Stop,Go) and (Go,Stop)
- identifies_one: Gets one of the two equilibria
- identifies_pattern: Recognizes one stops, one goes
- says_both_stop: Says (Stop,Stop) - incorrect
- confused: Other answers
- set_language: Language preference
- off_topic: Unrelated
feedback_tokens_for_ai: |
Correct equilibria: (Stop, Go) and (Go, Stop)
If correct:
- Excellent! Two Nash Equilibria where one stops, one goes.
- Neither wants to unilaterally change.
- This is like traffic lights solving coordination!
If says both stop:
- That seems safe but it's NOT Nash Equilibrium!
- If both stop, either could switch to Go and get +1 instead of -1.
- Nash requires no one wants to unilaterally deviate.
Explain why the two asymmetric outcomes are stable.
buckets:
- correct_both
- identifies_one
- identifies_pattern
- says_both_stop
- confused
- set_language
- off_topic
transitions:
correct_both:
ai_feedback:
tokens_for_ai: |
Perfect! Two Nash Equilibria: (Stop,Go) and (Go,Stop).
In each, no driver wants to unilaterally change.
Both stopping is NOT equilibrium - either would want to go!
This coordination problem is solved by traffic lights in reality!
metadata_add:
score: "n+2"
concepts_mastered: "n+1"
next_section_and_step: dominant_strategies:step_1
identifies_one:
ai_feedback:
tokens_for_ai: |
Good! You found one equilibrium.
But there's symmetry - also a Nash Equilibrium where roles reverse!
Both (Stop,Go) and (Go,Stop) are stable.
In each, neither wants to unilaterally change.
metadata_add:
score: "n+1"
next_section_and_step: dominant_strategies:step_1
identifies_pattern:
ai_feedback:
tokens_for_ai: |
Right idea - one stops, one goes!
Specifically: (Stop,Go) and (Go,Stop) are both Nash Equilibria.
Neither driver wants to change their strategy given the other's.
This is a coordination game solved by conventions (like traffic lights!).
next_section_and_step: dominant_strategies:step_1
says_both_stop:
ai_feedback:
tokens_for_ai: |
Seems safe, but NOT Nash Equilibrium!
At (Stop,Stop), either driver could switch to Go:
Get +1 instead of -1 while other stays stopped.
Nash requires no one wants to deviate.
The equilibria are (Stop,Go) and (Go,Stop).
next_section_and_step: nash_equilibrium:step_1
confused:
content_blocks:
- "Check each outcome: Can any player improve by switching?"
- "Nash Equilibrium: No player wants to unilaterally change strategy"
- "Hint: One driver stops, one goes (two ways to do this)"
next_section_and_step: nash_equilibrium:step_1
set_language:
content_blocks:
- "Language updated!"
metadata_add:
language: "the-users-response"
counts_as_attempt: false
next_section_and_step: nash_equilibrium:step_1
off_topic:
content_blocks:
- "Find outcomes where neither driver would want to change their choice given what the other is doing."
next_section_and_step: nash_equilibrium:step_1
- section_id: dominant_strategies
title: Dominant Strategies
steps:
- step_id: step_1
title: Always-Best Strategies
content_blocks:
- "## Dominant Strategies: No-Brainer Moves 💪"
- ""
- "**Definition:**"
- "A dominant strategy is one that's best regardless of what other players do."
- ""
- "**If you have a dominant strategy, PLAY IT!**"
- ""
- "**In Prisoner's Dilemma:**"
- "Betraying is a dominant strategy for both players."
- "- Better if opponent stays silent: 0 < 1"
- "- Better if opponent betrays: 2 < 3"
- "- Always better!"
- ""
- "**Dominant Strategy Equilibrium:**"
- "When all players have dominant strategies, the outcome is certain!"
- "- Everyone plays their dominant strategy"
- "- This is always a Nash Equilibrium"
- "- But Nash Equilibrium doesn't always involve dominant strategies"
- ""
- "**Example without dominant strategies:**"
- ""
- "Rock-Paper-Scissors:"
- "- No strategy is always best"
- "- Best strategy depends on opponent's choice"
- "- Optimal: Randomize (mixed strategy)"
- ""
- "**Why dominant strategies matter:**"
- "- Simplify analysis (easy to predict)"
- "- Stable and robust"
- "- Used in mechanism design (incentive compatibility)"
question: "A company must choose High Price or Low Price. If both choose High, each earns $100. If both choose Low, each earns $50. If one chooses Low and other High, the low pricer earns $120 and the high pricer earns $20. Does either company have a dominant strategy? If so, what is it?"
tokens_for_ai: |
Payoff matrix:
Company B
High Low
Company A High (100,100) (20,120)
Low (120,20) (50,50)
For Company A:
- If B plays High: Low gives 120 > High gives 100 → Low better
- If B plays Low: Low gives 50 > High gives 20 → Low better
- Low DOMINATES High
Same logic for Company B.
Both have dominant strategy: Low Price
Look for recognition that Low dominates High.
Categorize as:
- correct_both_low: Says Low is dominant strategy for both
- says_low: Identifies Low without full explanation
- says_high: Says High (incorrect - not dominant)
- says_no_dominant: Says no dominant strategy exists
- unclear: Confused answer
- set_language: Language preference
- off_topic: Unrelated
feedback_tokens_for_ai: |
Correct: Low is dominant strategy for BOTH companies.
If correct:
- Excellent! Low dominates High for both.
- If opponent prices High: 120 > 100 (Low better)
- If opponent prices Low: 50 > 20 (Low better)
- Result: Both price low, earn 50 each (could've earned 100 each!)
- This is another Prisoner's Dilemma structure!
If wrong:
- Check each scenario.
- Show that Low always outperforms High regardless of opponent.
- Explain this leads to (Low,Low) equilibrium.
Connect to PD structure.
buckets:
- correct_both_low
- says_low
- says_high
- says_no_dominant
- unclear
- set_language
- off_topic
transitions:
correct_both_low:
ai_feedback:
tokens_for_ai: |
Perfect analysis!
Low DOMINATES High for both companies.
No matter what opponent does, Low is better.
Result: (Low,Low) = $50 each.
If they could cooperate: (High,High) = $100 each!
This is Prisoner's Dilemma in business form!
metadata_add:
score: "n+2"
concepts_mastered: "n+1"
next_section_and_step: conclusion:step_1
says_low:
ai_feedback:
tokens_for_ai: |
Correct! Low is the dominant strategy.
Why? Check both scenarios:
If opponent prices High: 120 (Low) > 100 (High)
If opponent prices Low: 50 (Low) > 20 (High)
Always better! This is another PD structure.
metadata_add:
score: "n+1"
next_section_and_step: conclusion:step_1
says_high:
ai_feedback:
tokens_for_ai: |
High would be great if both could commit!
But it's NOT dominant. Check:
If opponent prices Low: 20 (High) < 120 (Low)
Low is better regardless of opponent.
This is why cartels are unstable!
next_section_and_step: dominant_strategies:step_1
says_no_dominant:
ai_feedback:
tokens_for_ai: |
Actually, there IS a dominant strategy!
Compare for Company A:
- If B plays High: Low(120) > High(100)
- If B plays Low: Low(50) > High(20)
Low is always better! Same for Company B.
next_section_and_step: dominant_strategies:step_1
unclear:
content_blocks:
- "For dominant strategy, check: Is one choice ALWAYS better than the other?"
- "Compare Low vs High when opponent plays High, then when opponent plays Low"
next_section_and_step: dominant_strategies:step_1
set_language:
content_blocks:
- "Language updated!"
metadata_add:
language: "the-users-response"
counts_as_attempt: false
next_section_and_step: dominant_strategies:step_1
off_topic:
content_blocks:
- "For each company, which strategy is better regardless of what the opponent does?"
next_section_and_step: dominant_strategies:step_1
- section_id: conclusion
title: Game Theory Foundations
steps:
- step_id: step_1
title: Strategic Thinking
content_blocks:
- "## Congratulations, Game Theorist! 🎓🎮"
- ""
- "**You've mastered the fundamentals!**"
- ""
- "**What you've learned:**"
- "✓ Prisoner's Dilemma (cooperation vs self-interest)"
- "✓ Nash Equilibrium (stable strategy profiles)"
- "✓ Dominant strategies (always-best moves)"
- "✓ How to analyze strategic situations"
- "✓ Why individually rational choices can lead to bad collective outcomes"
- ""
- "**Key insights:**"
- "- Strategic thinking requires considering others' incentives"
- "- Equilibrium ≠ optimal (Prisoner's Dilemma!)"
- "- Dominant strategies simplify prediction"
- "- Coordination problems have multiple equilibria"
- "- Institutions and repeated play can enable cooperation"
- ""
- "**Real-world applications:**"
- "- Understanding why cartels fail"
- "- Recognizing arms race dynamics"
- "- Designing better mechanisms (auctions, voting)"
- "- Building institutions that align incentives"
- ""
- "**Next steps:**"
- "- Game Theory 201: Mixed strategies and repeated games"
- "- Look for strategic interactions in daily life"
- "- Think about how to align individual and collective interests"
question: "How has learning game theory changed how you think about strategic situations? Give an example where you might apply these concepts."
tokens_for_ai: |
This is a reflection question.
Look for:
- Recognition of strategic interdependence
- Understanding that others' incentives matter
- Application to real situations
- Appreciation of conflict between individual/collective rationality
Categorize as:
- excellent_reflection: Insightful application showing deep understanding
- practical_application: Good real-world example
- general_reflection: Acknowledges usefulness
- brief_response: Short but relevant
- set_language: Language preference
- off_topic: Unrelated
feedback_tokens_for_ai: |
Provide encouraging feedback!
Validate their example/reflection.
Emphasize key takeaway: think about others' incentives!
Game theory helps predict behavior and design better systems.
Mention Game Theory 201 for deeper concepts.
Celebrate their foundational understanding!
buckets:
- excellent_reflection
- practical_application
- general_reflection
- brief_response
- set_language
- off_topic
transitions:
excellent_reflection:
ai_feedback:
tokens_for_ai: |
Fantastic insight!
Reference their example specifically.
You now think strategically about interdependent decisions!
This foundation enables understanding mechanism design, auctions, bargaining.
Ready for Game Theory 201 when you are!
metadata_add:
activity_completed: "true"
practical_application:
ai_feedback:
tokens_for_ai: |
Great application!
Acknowledge their example.
Game theory is everywhere once you start looking!
Understanding incentives helps predict and influence behavior.
Excellent work mastering the fundamentals!
metadata_add:
activity_completed: "true"
general_reflection:
ai_feedback:
tokens_for_ai: |
Good reflection!
The core lesson: always consider others' incentives.
Strategic interactions are everywhere - business, politics, daily life.
You've built a strong foundation in game theory!
metadata_add:
activity_completed: "true"
brief_response:
ai_feedback:
tokens_for_ai: |
Thank you for completing Game Theory 101!
You've learned to think strategically about interactive decisions.
These concepts underpin economics, politics, and much more!
metadata_add:
activity_completed: "true"
set_language:
content_blocks:
- "Language updated!"
metadata_add:
language: "the-users-response"
counts_as_attempt: false
next_section_and_step: conclusion:step_1
off_topic:
content_blocks:
- "Reflect: How might understanding incentives and strategic interaction help you in real-world situations?"
next_section_and_step: conclusion:step_1